Can Smaller Marketing Budgets Produce Greater Returns?
Can Smaller Marketing Budgets Produce Greater Returns? Can Less Ads Mean More Gains for Brands?
Nobody likes a budget cut.
For marketers, getting their ad dollars slashed can be particularly painful. According to Pepper Global, 37 percent of marketers say that budget constraints keep them from carrying out an effective marketing automation strategy. Meanwhile, almost a third say that securing a sufficient budget is their top marketing challenge.
But do smaller marketing budgets have to mean less effective advertising?
Not necessarily. Marketers with small budgets—or those dealing with budget cuts—can actually see a greater return on their investments. How? By coupling location data with other critical insights, brands can make sure each and every ad dollar they spend is working to the fullest.
The first thing a marketer with a reduced budget should do is identify—and eliminate—waste.
By coupling their proximity campaigns with third-party data sources, brands can find out where they might not be making the best use of their investment. For example, a luxury retailer located in a shopping mall might be serving ads to anyone who comes nearby, but how many of those shoppers are actually interested in—or can even afford—their high-end products?
Instead of wasting ad impressions on someone that might never buy one of their products, the luxury retailer can hyper-target an ideal subset of consumers. For example, using previous purchase data, the brand can identify consumers who have shopped at high-end retailers in the past. By serving ads only to individuals with a preference for luxury retailers, the brand will reduce wasted spend—enticing only likely buyers to visit the store.
Retailers can also reduce waste and hyper-target their campaigns by capitalizing on historical location data. By understanding how—and where—consumers historically spend their time, advertisers can gain useful insights to craft high-performing ad campaigns.
For example, if a consumer drives to the local school every morning before heading to the gym, what can a retailer learn about them? That they are likely a parent dropping the kids off at school before getting in some exercise. This consumer might be a perfect target audience for a children’s clothing retailer. A sports vehicle brand trying to sell more two-seaters, on the other hand, might do well to avoid them.
Similarly, a mountain sports brand can use historical location data to identify their ideal sporty audience. They can, for instance, target only those consumers who’ve been seen at a ski resort, a national park cabin, or a competitor’s outdoor sports store.
By knowing where consumers have been, brands can make sure they are targeting only those consumers who are most likely to convert.
Cross-pollinate Your Campaigns
Some of the most valuable insights about consumers don’t come from distant data sources at all. Instead, they come a brand’s campaign itself.
Let’s say a large CPG brand runs a campaign to boost foot traffic. After a successful campaign, they take a look at all the people they converted, perhaps finding that 70 percent of them go to the gym regularly. The retailer can use these newfound insights to inform the next campaign cycle, such as suggesting they try a sports beverage or protein bar.
By leveraging knowledge gained from one campaign and using it for another, advertisers can make sure they are iteratively improving their advertising—and boosting returns.